Loss
MAE is less sensitive to outliers but I am still trying to mae as my loss function? Why do you think someone might choose MAE as the loss but still monitor MSE as a metric? What behavior during training might that help catch?
My data distribution is really sparse so as my data distribution is more sparse i choose mae over mse. Basically, it will app
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